Regular physical activity (PA) is known to reduce the risk of serious community-acquired infections. We examined the association of PA with the morbidity and mortality resulting from coronavirus disease (COVID-19) infection in the South Korean population. Patients who tested positive for severe acute respiratory coronavirus 2 and who underwent public health screening between 2014 and 2017 (n = 6288) were included. Age- and sex-matched controls (n = 125,772) were randomly selected from the Korean National Health Insurance Service database. Leisure-time PA was assessed using a self-reported questionnaire. The mean PA levels were lower in the patient than in the control group (558.2 ± 516.3 vs. 580.2 ± 525.7 metabolic equivalent of task (MET)-min/week, p = 0.001). Patients with moderate to vigorous PA (MVPA) were associated with a lower risk of COVID-19 morbidity (odds ratio (OR), 0.90; 95% confidence interval (CI), 0.86–0.95). In addition, a standard deviation (SD) increment in MET/week (525.3 MET-min/week) was associated with a 4% decrease in the risk of COVID-19 morbidity (OR, 0.96; 95% CI, 0.93–0.99). MVPA and an SD increment in MET/week were associated with lower mortality (MVPA: OR, 0.47; 95% CI, 0.26–0.87; per SD increment: OR, 0.65; 95% CI, 0.48–0.88). Higher levels of regular PA were associated with a lower risk of COVID-19 infection and mortality, highlighting the importance of maintaining appropriate levels of PA along with social distancing amid the COVID-19 pandemic.

Background/Aims: We measured the association between underlying chronic hepatitis B (CHB) and antiviral use with infection rates among patients who underwent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. Methods: In total, 204,418 patients who were tested for SARS-CoV-2 between January and June 2020 were included. For each case patient (n = 7,723) with a positive SARS-CoV-2 test, random controls (n = 46,231) were selected from the target population who had been exposed to someone with coronavirus disease 2019 (COVID-19) but had a negative SARS-CoV-2 test result. We merged claim-based data from the Korean National Health Insurance Service database collected. Primary endpoints were SARS-CoV-2 infection and severe clinical outcomes of COVID-19. Results: The proportion of underlying CHB was lower in COVID-19 positive patients (n = 267, 3.5%) than in COVID-19 negative controls (n = 2482, 5.4%). Underlying CHB was associated with a lower SARS-CoV-2 positivity rate, after adjusting for comorbidities (adjusted odds ratio [aOR] 0.65; 95% confidence interval [CI], 0.57–0.74). Among patients with confirmed COVID-19, underlying CHB tended to confer a 66% greater risk of severe clinical outcomes of COVID-19, although this value was statistically insignificant. Antiviral treatment including tenofovir and entecavir was associated with a reduced SARS-CoV-2 positivity rate (aOR 0.49; 95% CI, 0.37–0.66), while treatment was not associated with severe clinical outcomes of COVID-19. Conclusions: Underlying CHB and antiviral agents including tenofovir decreased susceptibility to SARS-CoV-2 infection. HBV coinfection did not increase the risk of disease severity or lead to a worse prognosis in COVID-19.

Gwon JG, et al. J Korean Surg Soc. 2012 Sep;83(3):171-174. http://dx.doi.org/10.4174/jkss.2012.83.3.171

Accurate measurement of abdominal aortic aneurysm is essential for selecting suitable stent-grafts to avoid complications of endovascular aneurysm repair. However, the conventional image-based measurements are inaccurate and time-consuming. We introduce the automated workflow including semantic segmentation with active learning (AL) and measurement using an application programming interface of computer-aided design. 300 patients underwent CT scans, and semantic segmentation for aorta, thrombus, calcification, and vessels was performed in 60–300 cases with AL across five stages using UNETR, SwinUNETR, and nnU-Net consisted of 2D, 3D U-Net, 2D-3D U-Net ensemble, and cascaded 3D U-Net. 7 clinical landmarks were automatically measured for 96 patients. In AL stage 5, 3D U-Net achieved the highest dice similarity coefficient (DSC) with statistically significant differences (p < 0.01) except from the 2D–3D U-Net ensemble and cascade 3D U-Net. SwinUNETR excelled in 95% Hausdorff distance (HD95) with significant differences (p < 0.01) except from UNETR and 3D U-Net. DSC of aorta and calcification were saturated at stage 1 and 4, whereas thrombus and vessels were continuously improved at stage 5. The segmentation time between the manual and AL-corrected segmentation using the best model (3D U-Net) was reduced to 9.51 ± 1.02, 2.09 ± 1.06, 1.07 ± 1.10, and 1.07 ± 0.97 min for the aorta, thrombus, calcification, and vessels, respectively (p < 0.001). All measurement and tortuosity ratio measured − 1.71 ± 6.53 mm and − 0.15 ± 0.25. We developed an automated workflow with semantic segmentation and measurement, demonstrating its efficiency compared to conventional methods.